Data capture systems can typically embed tags, headers and/or metadata along with the data to provide contextual information for the data. Such contextual information can include time stamps, frame identifiers and the like. However, such contextual information is only useful to distinguish one piece of data from another according to the information. For example, for a time stamp, this information only provides the ability to determine what piece of data was captured at what point in time.
Meanwhile, in a video data capture system for example, it is often desirable to rapidly identify images that are similar in appearance rather than those that just occur at a given time or at a certain number in a sequence. Often, when this is desired during post-capture analysis, complex image processing must be performed on all the data to search for and identify frames having the image of interest. This processing can take considerable amounts of time and require sophisticated image processing tools.
Accordingly, it would be desirable if there were a way to qualitatively characterize data during a capture process to facilitate subsequent retrieval during data analysis. It would be further desirable if this characterization process could be done without requiring complex processing power, and if it could be done in real-time while the data is being captured.